In this study, a Julia programming language based system description language and simulation environment that enables fast and effective system simulations together with online and offline data analysis is introduced. In the simulation environment developed, it is possible to simulate discrete time or continuous time, static or dynamical systems. In particular, it is possible to simulate dynamical systems modeled by different types of equations, such as the ordinary differential, random ordinary differential, stochastic differential, differential-algebraic, delayed differential equations, and discrete-time difference equations. During the simulation, the data flowing through the links of the model can be processed online and offline, and specialized analysis can be performed. These analyzes can also be enriched with plugins that can be easily defined using the standard Julia library or various Julia packages. The simulation is performed by evolving the model components individually and parallelly between sampling time intervals. The independent evolution of the components allows the simulation of the models consisting of the components represented by different mathematical equations, while the parallel evolution of components increases the simulation speed.